Sperm Recovery and Evaluation in Domestic Species: Challenges and Current Practices

ABSTRACT

Semen collection is a key step in the development of assisted reproductive technologies (ARTs) in domestic mammals, as the collection method determines the functionality and fertility of the sperm. The artificial vagina or manual collection yields ejaculates similar to those obtained during natural mating, although they require prior training to enable semen collection. When semen collection cannot be achieved using the aforementioned techniques, alternative methods such as electroejaculation may be employed. This method has been associated with increased stress and pain in animals; therefore, it should be restricted to specific cases and combined with rectal massage and the administration of sedatives. Finally, spermatozoa can be recovered post‐mortem from the cauda epididymis where they are already capable of fertilizing oocytes. After sperm collection, the evaluation of sample quality is essential to ensure success following the application of ARTs. Alongside the techniques commonly used in animal reproduction laboratories, more advanced and objective methodologies have been developed using technologies such as computer‐assisted semen analysis (CASA) or flow cytometry. CASA systems enable the quantitative assessment of sperm motility at the individual cell level and the identification of sperm subpopulations associated with fertility. In parallel, flow cytometry expands analytical capabilities by allowing the simultaneous evaluation of multiple parameters indicative of sperm function in a single cell. This review summarizes the main methods of sperm collection across domestic mammal species, describing the respective advantages and disadvantages. Additionally, it provides an overview of the current methodologies for semen quality assessment and highlights the need for further advances in the identification of reliable fertility biomarkers.

1. Introduction

To successfully apply assisted reproductive technologies (ARTs), including artificial insemination (AI), sperm cryopreservation, in vitro fertilization (IVF), intracytoplasmic sperm injection (ICSI), and sperm sexing, the availability of high‐quality sperm samples is essential.

Historically, sperm collection represented a major limiting factor in the development of ARTs in the early 20th century. Initial approaches included rectal massage of the accessory sex glands in cattle (Ivanoff 1907) and semen recovery from sponges following mating in mares (Ivanoff 1922). The development of the first artificial vagina (AV) for bulls in 1914 (Walton 1933) marked a turning point, as this method was subsequently adapted to other species, enabling wider implementation of AI in domestic animals. However, in species where semen collection was not routinely performed, animals were not often conditioned for AV use. In this context, the electroejaculator developed by Dziuk et al. (1954) provided a valuable alternative, particularly for wildlife species in which training is not feasible.

In parallel, the recovery of spermatozoa from the cauda epididymis emerged as a valuable approach for preserving genetic material (Mujitaba et al. 2023). From the 1960s onwards, research focused on their physiology in laboratory animals and livestock (Amann et al. 1973), and by the 1970s and 1980s, it was demonstrated that these spermatozoa retained fertilizing ability. Although not the method of choice for sperm collection, this approach allows for the use of genetic material from individuals after death or castration, thereby extending its application in ARTs.

The assessment of sperm quality has also undergone substantial evolution over time. Since the first microscopic observations of ‘animalcules’ by Antonie van Leeuwenhoek in the 17th century (Andrade‐Rocha 2017), methodological advances have progressively improved methods for assessing sperm quality. With the first applications of AI in the 19th century, the need to establish minimum criteria for semen quality became increasingly evident. This led, between the 1930s and 1950s, to the routine implementation of techniques such as cell counting chambers, subjective microscopic assessment of motility and staining methods for sperm morphology (Andrade‐Rocha 2017). More recently, sperm evaluation has moved towards more objective and quantitative approaches, incorporating technologies such as computer‐assisted sperm analysis (CASA) for the assessment of motility (Amann and Waberski 2014), as well as flow cytometry combined with fluorescent probes (Peña et al. 2018), which enable the evaluation of parameters ranging from DNA integrity to sperm cellular attributes, including membrane condition or mitochondrial activity and specific proteins involved in sperm function.

Given the diversity of sperm collection and evaluation techniques, and their potential impact on sperm quality and reproductive outcomes, this review aims to provide an overview of current methods used in domestic mammals, with particular emphasis on their practical implications for ARTs. Because semen quality assessment is strongly influenced by the way the sample is collected, handled and processed, this review considers sperm recovery and semen evaluation as closely connected steps rather than independent procedures. This applied perspective is further developed in the final section, where standardized artificial insemination center workflows are contrasted with field conditions.

1.1. Literature Search Strategy

This manuscript was developed as a structured narrative review rather than as a systematic review or quantitative meta‐analysis. The objective was to provide a balanced and transparent synthesis of the available literature on sperm recovery methods and semen quality assessment in domestic mammals. To improve clarity and traceability in the selection of sources, the search strategy was designed according to general recommendations for narrative and integrative literature reviews (Snyder 2019) and was guided, when appropriate, by the principles of transparent reporting proposed in the PRISMA statement (Page et al. 2021). Relevant publications were identified through searches in PubMed/MEDLINE, Scopus, Web of Science and Google Scholar. Search terms were combined according to the topic being explored and included: ‘semen collection’, ‘sperm recovery’, ‘artificial vagina’, ‘manual collection’, ‘electroejaculation’, ‘transrectal massage’, ‘epididymal sperm’, ‘post‐mortem sperm recovery’, ‘domestic mammals’, ‘bull’, ‘ram’, ‘goat buck’, ‘boar’, ‘stallion’, ‘dog’, ‘cat’, ‘rabbit’, ‘computer‐assisted sperm analysis’, ‘CASA’, ‘flow cytometry’, ‘fertility biomarkers’, ‘seminal plasma’, ‘proteomics’, ‘metabolomics’, ‘artificial intelligence’ and ‘machine learning’. In addition, the reference lists of selected reviews and original research articles were examined manually to retrieve further relevant studies. The selection focused primarily on peer‐reviewed articles involving domestic mammalian species, especially studies that provided comparative or functional information on sperm collection procedures, semen quality, sperm physiology, cryopreservation outcomes, fertility, animal welfare, or methodological standardization. Studies performed in closely related wild or semi‐domestic species were also considered when they offered relevant mechanistic or technical insights applicable to domestic animals, particularly in relation to electroejaculation, transrectal massage, or epididymal sperm recovery. The final body of literature included historical landmark studies, species‐specific experimental work, and recent contributions addressing omics‐based biomarkers and automated or AI‐assisted semen analysis.

2. Sperm Collection Methods

A range of sperm collection methods is available, with their suitability largely dictated by species‐specific constraints. In domestic animals, the most widely employed approaches include manual stimulation (e.g., boar and dog) and AV collection (e.g., ruminants, horse and rabbit). These techniques generally allow the recovery of ejaculates that closely resemble those obtained during natural mating, preserving seminal characteristics. However, both methods require prior training of the animal.

In cases where animals are not trained or cannot be trained, alternative approaches such as electroejaculation (EE) may be required. Additionally, epididymal sperm recovery represents a valuable option following the death of high‐value animals, allowing the preservation of their genetic material. Therefore, selecting the most appropriate method involves balancing practicality, animal welfare and the quality of resulting sperm samples.

2.1. Sperm Collection by Manual Stimulation

In pigs, semen is typically collected using the gloved‐hand technique, which involves manual stimulation of the boar's penis during mounting on a dummy sow or phantom. Semen quality is influenced by several management factors, particularly collection frequency and social conditions. An optimal interval of 2–5 days has been described, as shorter intervals result in reduced semen volume, sperm concentration and motility, as well as an increased proportion of immature spermatozoa with proximal cytoplasmic droplets (Pinart and Puigmolé 2013). Conversely, excessively high collection frequencies, such as daily collection, negatively affected both sperm quality and fertility (Frangez et al. 2005). In addition to these frequency‐related effects, the social environment also plays a key role in reproductive performance. Social restriction from 3 to 30 weeks of age reduces sexual activity (Hemsworth and Tilbrook 2005), and boars raised under such conditions produce lower semen volumes compared to those housed in the presence of other males and with minimal physical contact with sows (Trudeau and Sanford 1990).

In dogs, semen is most commonly collected by manual stimulation, typically performed in the presence of a bitch in estrus. The procedure involves a vigorous massage of the penis through the prepuce at the level of the bulbus glandis until erection is achieved. The prepuce is then retracted beyond the bulbus glandis while maintaining digital pressure behind this structure, followed by a caudal rotation of the penis of approximately 180°, thereby inducing ejaculation (Kutzler 2005).

In bulls, transrectal massage has been used as a semen collection method. When performed by placing the thumb and little finger in direct contact with the ampulla and applying a gentle cranial‐to‐caudal movement, it has been proved to be more effective than a vigorous 2 min back‐and‐forth stimulation of the pelvic urethra, prostate and ampulla (Palmer et al. 2005). This method was not influenced by bull age, breed or operator, but it requires more time and, generally yields ejaculates with lower sperm concentration, motility and viability compared with EE (Palmer et al. 2005). A refined version of this technique, the ultrasound‐guided transrectal massage (TUMASG), has been widely described in wild ruminants (Santiago‐Moreno et al. 2013; Ungerfeld et al. 2015). This procedure involves massaging the ampullae of the ductus deferens using an ultrasound probe, combined with manual stimulation of the bulbourethral glands and the application of pressure against the pubic symphysis, while simultaneously stimulating the urethral tract to facilitate the movement of ejaculatory fluids (Abril‐Sánchez et al. 2019). Although TUMASG alone is not sufficient to obtain semen samples in goat bucks, its combination with EE reduces the number of electrical stimuli required compared to EE used alone. In addition, some stress indicators, such as vocalization, blood cortisol concentration and heart rate, were lower during TUMASG than during EE, and no differences in sperm quality were observed (Abril‐Sánchez et al. 2017).

Overall, manual and stimulation‐based methods provide practical semen collection in specific contexts, although their efficiency and impact on sperm quality vary depending on species and management conditions.

2.2. Sperm Collection by Artificial Vagina

AVs are devices designed to simulate copulation, allowing semen to be collected under conditions that closely resemble natural mating. A recent review by (Rich and Orbach 2025) highlighted that AV design varies across species in terms of size, shape, components and material composition. Nevertheless, most AVs share a common structure consist of a rigid outer structure and a flexible inner liner made of rubber/latex or plastic and are typically filled with warm water and air to maintain temperature and turgidity, thereby mimicking the female reproductive tract.

The main limitation of the AV‐based collection is the need for prior training of males (Ambrosi et al. 2018). In addition, for some species, effective semen collection requires the presence of females, whether in estrus or not, as well as olfactory cues such as urine, or even the use of dummies. Moreover, considerable variability has been reported in both the training process and the frequency of sexual behavioural responses, although it has been demonstrated that all young rams can be eventually trained to ejaculate using an AV (Ambrosi et al. 2018).

Beyond training, management factors such as collection frequency also play a critical role in determining semen quality, although their effects are highly species‐dependent. For instance, increased collection frequency has been associated with improved foaling rates in horses (Sieme et al. 2004), whereas in rams it led to reduced semen quality and antioxidant capacity, ultimately minimizing cryoresistance (Palacin‐Martinez et al. 2022). Furthermore, changes in seminal plasma composition associated with collection frequency have been linked to differences in storage capacity at 15°C (Moula et al. 2022). These findings highlight the need to optimize collection protocols based on species‐specific physiology.

The relative effectiveness of AV collection compared to other methods also varies across species. In bulls, AV collection is widely used and has been associated with improved semen quality for both fresh and frozen–thawed samples, and higher conception rates compared to EE, regardless of age (Nadaf et al. 2022). In small ruminants, the use of AV is also well established due to the relative ease of training in this species. In sheep, most sperm parameters do not differ between AV and EE in fresh and frozen–thawed samples, although higher sperm concentration has been reported with AV collection (Jiménez‐Rabadán et al. 2016). In contrast, Marco‐Jiménez et al. (2005) reported a lower proportion of viable spermatozoa with intact acrosomes after thawing when using AV related to EE. However, in goats bucks, AV collection generally results in improved sperm quality compared to EE, with higher values observed for most parameters except kinematic traits in both fresh and frozen–thawed samples (Jiménez‐Rabadán et al. 2012).

In horses, semen collection using the AV is also the standard method. Within this context, factors such as device temperature do not appear to influence semen quality (Hillman et al. 1980). In addition, alternative systems based on the use of phantoms have been developed to further refine ejaculate collection. For example, Lindeberg et al. (1999) developed a phantom that allows the separation of the pre‐ejaculatory, sperm‐rich and gel fractions. Using this approach, they observed a lower total volume but higher sperm concentration in the sperm‐rich fraction compared to conventional AV, although no differences were reported in progressive motility of cooled and frozen–thawed semen between methods.

In contrast, the use of AV in other species remains limited. In pigs, although the gloved‐hand technique is the preferred method, alternative approaches, like the commercial device Collectis, have been tested with moderate success. This device is similar to an AV, as it regulates air pressure and vacuum and has been shown to reduce labor and collection time compared with the gloved‐hand technique, without affecting semen production (Barrabes‐Aneas et al. 2008).

In cats, semen collection is typically performed using EE, although AV collection has also been explored with variable results. Sojka et al. (1970) collected semen by AV from three animals, and Dooley and Pineda (1986) reported lower volume and pH, but similar sperm motility and viability in semen collected using this method.

In rabbits, semen collection by AV is the only well‐documented method, and available studies focus mainly on factors influencing ejaculate characteristics rather than alternative collection techniques. Indeed, Rodríguez‐De Lara et al. (2010) assessed the influence of female stimulation on ejaculatory output and reported that sperm motility increased in the second ejaculate when males were exposed to females.

2.3. Sperm Collection by Electroejaculation

Semen collection by EE represents an alternative when animals are not trained to ejaculate into an AV or when other techniques are not feasible. This procedure is performed using an electroejaculator, a device equipped with a rectal probe containing electrodes that deliver controlled electrical stimuli. The probe is inserted into the rectum, where it stimulates the nerves innervating the reproductive tract, thereby inducing ejaculation. Although protocol varies depending on the species (Abril‐Sánchez et al. 2019), effective stimulation generally involves a gradual increase in voltage interspersed with rest periods. In bulls, ejaculation is typically achieved with stimuli below 8–9 V (Palmer et al. 2005), whereas in rams and goat bucks it can be induced with lower voltages (Jiménez‐Rabadán et al. 2016).

Despite its practical utility, EE raises important animal welfare concerns. Several studies have demonstrated that this technique induces stress and pain, as evidenced by increases in physiological parameters such as heart rate, respiratory rate, rectal temperature and cortisol levels. In addition, alterations in haematocrit and haemoglobin, along with increased creatine kinase levels indicative of muscle damage, have been reported (Ungerfeld et al. 2015). These welfare concerns have also influenced the legal and professional status of EE, which varies considerably among countries. In Europe, current recommendations for sheep and goats restrict its use to exceptional diagnostic situations, when no alternative method is available and the procedure can be performed under strict veterinary control; moreover, semen collection by EE is banned in several countries, including Denmark and the Netherlands (EURCAW Ruminants and Equines 2024). In Canada, EE in cattle, sheep and goats is considered a veterinary procedure that requires veterinary involvement or supervision, and less invasive alternatives are recommended whenever feasible (Canadian Veterinary Medical Association 2025). Similar principles are reflected in guidelines for artificial insemination centers in the United States, where EE should be used only when AV collection is unsafe or impossible and after reasonable attempts to collect semen by AV have failed (National Association of Animal Breeders 2026). In Australia, its use in bulls, rams and bucks is also linked to appropriate veterinary expertise and direct supervision (Australian Veterinary Association, n.d.). Taken together, these examples show that EE should not be viewed as a routine or universally interchangeable collection method, but as a welfare‐sensitive procedure whose use must be interpreted within the local legal, ethical and professional context. At the procedural level, these considerations mean that the use of EE should be supported by a well‐defined reproductive, genetic, or conservation objective, performed only by trained personnel, and monitored using predefined behavioural and physiological criteria. Where feasible, less invasive alternatives or complementary approaches, including rectal massage, transrectal ultrasound‐guided massage of the accessory sex glands, or prior conditioning of males to artificial vagina collection, should be considered before resorting to EE. When EE is unavoidable, appropriate refinement measures, such as sedation, anaesthesia, or analgesia, should be evaluated according to species‐specific welfare requirements and experimental or clinical conditions (Falk et al. 2001; Abril‐Sánchez et al. 2019). These methodological considerations are also important when interpreting the quality of semen collected by EE. Two issues deserve particular attention: urine contamination and, in species with fractionated ejaculates, changes in the normal sequence or relative contribution of seminal fractions. The presence of urine in the ejaculate may be difficult to separate from true species‐ or protocol‐related differences in seminal plasma composition. Contaminated samples may show changes in colour, odour, pH and osmolality, and exposure to urine has been shown in dogs and horses to reduce sperm motility and compromise membrane or acrosomal integrity under non‐physiological osmotic conditions (Griggers et al. 2001; Santos et al. 2011). For this reason, studies using EE should report any visual or olfactory evidence of urine contamination, pH and osmolality when available, the criteria used to pool or discard fractions, and whether potentially contaminated fractions were processed separately.

A second issue, mainly documented in cervids but useful as comparative evidence, is that EE may alter the physiological order of ejaculate fractions. In red deer, ejaculates collected during the rut may include a sperm‐rich white fraction followed by a viscous, sperm‐free yellow or honey‐like fraction (Gizejewski et al. 2003). If accessory gland secretions are released earlier than expected or mixed disproportionately during EE, the final sample may differ from a physiological ejaculate in sperm concentration, viscosity, pH, motility and seminal plasma composition (Pintus and Ros‐Santaella 2014). This aspect is relevant when information from deer is extrapolated to semi‐domestic reindeer, a species in which reproductive anatomy, seasonality and ART development require specific consideration (Lindeberg et al. 2021; Nagy et al. 2021). Although domestic species do not all show the same degree of ejaculate fractionation, these findings reinforce the need to describe fraction sequence, pooling strategy and sample handling when interpreting semen obtained by EE. The physiological response to EE varies among species. In goat bucks, EE has been shown to increase vocalizations and cortisol concentrations compared to TUMASG (Abril‐Sánchez et al. 2017), while in sheep, it also increased heart rate (Orihuela et al. 2009). In bulls, adrenal progesterone has been identified as a more sensitive indicator of pain than cortisol when EE was performed (Falk et al. 2001) and its reduction following epidural anaesthesia further supports its use as a biomarker (Etson et al. 2004). Additionally, vocalization, particularly at higher electrical stimuli, is considered an indicator of pain in bulls (Falk et al. 2001).

In contrast, in some species, EE is routinely applied with fewer apparent adverse effects. In cats, it is considered the method of choice for semen collection, and repeated use of anaesthesia and electrical stimulation does not appear to impair ejaculatory capacity or cause harmful effects (Pineda et al. 1984). In this species, voltages above 2 V yield the highest number of spermatozoa, whereas urine contamination has been reported at voltages of 8 V (Pineda et al. 1984).

EE has also been evaluated in species for which alternative collection methods are available. In pigs, ejaculates can be obtained under anaesthesia without differences in volume, concentration, or sperm quality compared to conventional collection methods (Basurto‐Kuba and Evans 1981), although its practical use remains limited due to the efficiency of the gloved‐hand technique. Similarly, in dogs, EE under anaesthesia has been shown to produce semen samples comparable in total sperm count and motile spermatozoa to those obtained by manual stimulation (Ohl et al. 1994), although it is not routinely used.

With regard to semen quality, the effects of EE remain inconsistent across studies, likely due to differences in stimulation protocols, semen handling and extender composition.

In rams, some studies have reported that sperm concentration is the main parameter affected compared to AV collection, generally being lower in EE samples (Jiménez‐Rabadán et al. 2016), whereas others have observed improved post‐thaw semen quality, suggesting greater cryoresistance (Ledesma et al. 2015; Marco‐Jiménez et al. 2005).

In goat bucks, EE has been associated with higher ejaculate volume but lower sperm concentration and motility compared to AV, along with reduced viability and mitochondrial activity and increased chromatin damage after thawing (Jiménez‐Rabadán et al. 2016). Nevertheless, no differences in semen quality have been observed when EE is compared with TUMASG (Abril‐Sánchez et al. 2017).

In bulls, EE samples have shown higher sperm concentration and a greater proportion of motile and viable spermatozoa than those obtained by transrectal massage (Palmer et al. 2005), although poorer semen quality has been reported when compared to AV collection (Nadaf et al. 2022).

Finally, EE has been associated in cats with higher values for several sperm parameters compared to urethral catheterization (Jelinkova et al. 2018).

Overall, these findings indicate that the impact of EE on semen quality is highly species‐dependent, and no consistent pattern can be generalized. Therefore, EE represents a viable alternative for semen collection when semen cannot be obtained using other methods, although its application should be carefully optimized to minimize stress and pain while ensuring adequate semen quality.

2.4. Post‐Mortem Sperm Collection

Although post‐mortem sperm collection is not routinely used in domestic animals, it serves as an alternative when genetically valuable individuals are castrated, euthanized, or die unexpectedly.

Spermatozoa undergo maturation during their transit through the epididymis and are stored in its distal region, the cauda epididymidis. Spermatozoa recovered from this region are highly mature and capable of fertilizing oocytes (Bertol 2016). The main difference from ejaculated ones is that epididymal spermatozoa have not been exposed to seminal plasma. Spermatozoa can be recovered from the cauda epididymidis using different approaches. The simplest procedure consists of making small incisions in the cauda and releasing or gently scraping the sperm material into a suitable medium (García‐Álvarez, Maroto‐Morales, Martínez‐Pastor, Garde, et al. 2009). Alternatively, sperm can be obtained by retrograde flushing from the vas deferens towards the cauda epididymidis using an appropriate extender or washing medium (Garde et al. 1994). This approach generally provides cleaner samples and better sperm quality than recovery by epididymal incision (Martinez‐Pastor et al. 2006; Bruemmer 2006). More controlled perfusion or flushing systems have also been described, including the use of a peristaltic pump in experimental studies with epididymal spermatozoa from bulls, rabbits and rams (Dott et al. 1979). In small animals, flotation method is commonly used, involving minor incisions in the cauda epididymis followed by immersion in a Petri dish with medium that facilitates sperm release (Yu and Leibo 2002).

One of the main factors affecting the quality of epididymal sperm is the time elapsed between the animal's death and sperm recovery, as well as the storage temperature of the epididymis. Kaabi et al. (2003) observed in sheep that sperm remained viable up to 48 h after the animal's death and that sperm motility was better when epididymides were maintained at 5°C compared to room temperature. Furthermore, the fertilizing capacity of samples stored for up to 24 h was similar to that of ejaculated spermatozoa. However, other authors found in the same species that, although several sperm quality parameters were higher in epididymal samples, the ability to produce embryos in vitro was lower than that observed with ejaculated samples (García‐Álvarez, Maroto‐Morales, Martínez‐Pastor, Garde, et al. 2009).

These findings are consistent with those of Martins et al. (2009) in bulls, who found a lower percentage of embryos when using post‐mortem spermatozoa compared to those from ejaculate. However, no differences were observed when spermatozoa were stored within the epididymis for 24, 48, or 72 h at 5°C.

The effects of post‐mortem sperm recovery may also vary across species. In rams, no differences in sperm quality have been reported between the right and left epididymis (Bertol et al. 2016; Bertol 2016), whereas differences have been observed in bulls (Goovaerts et al. 2006). In horses, high‐quality spermatozoa have been obtained from the epididymis compared to those obtained by EE (Cary et al. 2004), even resulting in offspring following AI (Barker and Gandier 1957).

In dogs, the integrity of the acrosome and plasma membrane was maintained when sperm from cauda epididymides were stored for up to 48 h at 4°C, although motility decreased after the first 5 h of refrigeration (Yu and Leibo 2002). In cats, sperm from the corpus and cauda epididymis can also be used for AI (Axnér 2025). Overall, post‐mortem sperm collection represents a useful strategy for the preservation of genetic material, although its success depends on multiple factors, including recovery technique, storage conditions and species‐specific differences. A comparative overview of the sperm collection methods currently used in domestic mammals, including their main advantages, limitations and typical applications, is presented in Table 1.

TABLE 1.

Comparative synthesis of sperm collection methods in domestic mammals.

Collection method	Main species/setting	Main advantages	Main limitations and welfare concerns	Interpretative relevance for sperm quality
Manual stimulation/gloved‐hand/transrectal massage	Boar and dog routinely; transrectal massage in bulls and selected ruminants	Low equipment requirement; useful when animals are accustomed to handling; can approximate physiological ejaculation in species where manual collection is routine	Requires trained personnel and animal cooperation; libido and ejaculate yield are influenced by management factors, and transrectal massage may produce lower sperm concentration and motility than EE in bulls	Differences in volume and sperm concentration often reflect stimulation efficiency and accessory gland contribution rather than intrinsic sperm competence
Artificial vagina (AV)	Standard in bulls, rams, bucks, stallions and rabbits; limited or experimental use in cats and pigs	Most closely resembles natural mating; generally provides high‐quality ejaculates; compatible with AI‐center workflows and repeated collection	Requires animal training, teaser females or dummies in some species; collection frequency and training success are species‐dependent	Usually provides the best reference sample for comparing alternative methods, although collection frequency and sexual preparation must be standardized
Electroejaculation (EE)	Used when AV/manual collection is not feasible; common in untrained males, breeding soundness evaluation, cats and some field situations	Allows semen recovery from untrained or difficult‐to‐handle animals; useful when rapid collection is required	Welfare‐sensitive; may induce pain/stress responses; risk of urine contamination and non‐physiological seminal plasma contribution; legal acceptance varies between jurisdictions	Can alter volume, concentration, seminal plasma composition and cryoresistance; interpretation requires detailed reporting of stimulus protocol, sedation/anaesthesia and contamination
Post‐mortem epididymal recovery	Genetically valuable animals after death, castration or emergency salvage; applicable across domestic species	Preserves genetic material when ejaculated semen is unavailable; avoids welfare concerns after death; useful for germplasm banks	Sperm are not exposed to accessory gland seminal plasma; quality depends on time to recovery, temperature and retrieval method	Provides mature spermatozoa with different biochemical history from ejaculated sperm; comparisons with ejaculates must consider absence of seminal plasma and storage conditions

Note: The table summarizes the predominant use and interpretation of each method. Species‐specific exceptions are discussed in the text.

3. The Role of Seminal Plasma in Modulating Sperm Quality Across Different Sperm Collection Techniques

Interpreting the differences in sperm quality observed among different sperm collection methods requires consideration of the modulatory role of seminal plasma. Rather than acting merely as the medium in which spermatozoa are transported, seminal plasma is a complex biological fluid composed of proteins, lipids, metabolites, ions and other bioactive compounds that regulate key processes in sperm function, including motility, membrane stability, capacitation, acrosome reaction and interaction with the female reproductive tract (Juyena and Stelletta 2012; Rodríguez‐Martínez et al. 2021). Therefore, differences observed between samples obtained by different methods cannot be attributed solely to intrinsic spermatozoa characteristics, but also to the biochemical environment to which they are exposed following ejaculation or recovery.

Sperm collection methods influence not only the presence or absence of seminal plasma, but also its relative abundance and molecular composition. Samples obtained via manual stimulation or AV most closely recapitulate physiological ejaculation, whereas EE can often increase the proportion of seminal plasma and alter its composition due to direct electrical stimulation of the accessory sex glands (Abril‐Sánchez et al. 2019). Several studies have reported variations in both the ionic and protein fractions of seminal plasma in samples obtained via EE across different species, including increases in sodium concentration and low‐molecular‐weight proteins (Ledesma et al. 2014; Marco‐Jiménez et al. 2008; Sarsaifi et al. 2013, 2015).

The development of omics technologies has provided a deeper understanding of these differences, demonstrating that the collection method affects not only the abundance of individual compounds but also entire molecular profiles. In bulls, ejaculates obtained via AV contain a higher proportion of epididymal proteins, whereas EE is associated with a greater contribution of proteins from the accessory sex glands, reflecting differences in the relative inputs of the reproductive tract to seminal plasma composition (Rego et al. 2015). Similarly, recent studies in goat bucks have demonstrated that EE alters both the proteomic and metabolomic profiles of seminal plasma, affecting compounds related to membrane structure, energy metabolism and antioxidant capacity (Lv et al. 2024, 2025). Furthermore, multi‐omic approaches in this species have shown that, although differences between collection methods may be limited in fresh semen, they become more pronounced following cryopreservation. These variations are associated with differences in the relative abundance of proteins and metabolites involved in key metabolic pathways, such as the Krebs cycle, oxidative phosphorylation and the metabolism of glycine, serine and threonine, ultimately resulting in reduced functional preservation of EE samples (Li et al. 2024).

Samples of epididymal origin represent a unique scenario, as spermatozoa have not been exposed to fluids from the accessory sex glands, which may also influence their functional state. It has been demonstrated that seminal plasma proteins can exert protective effects, but only when spermatozoa have not previously interacted with them (Viana et al. 2022). Accordingly, it has been reported a lower response in ejaculated spermatozoa compared to those from the epididymis when incubated with binders of sperm proteins (BSPs) (Rodríguez‐Villamil et al. 2020).

Furthermore, seminal plasma contains extracellular vesicles (EVs), lipid bilayer structures, that contain regulatory molecules capable of modulating sperm physiology and fertilization capacity (Fazeli et al. 2025). Depending on the collection method, spermatozoa may be exposed to different populations of EVs. In post‐mortem collection, spermatozoa in contact with epididymal fluid are exposed primarily to epididymosomes, whereas ejaculated samples, obtained via AV or EE, also come into contact with EVs derived from species‐specific accessory sex glands. This interaction with different EVs modifies sperm function (Moya‐Fernández et al. 2025), reinforcing the role of the collection method as a key determinant of sperm quality and fertility.

4. Sperm Quality Evaluation

The assessment of sperm quality in domestic species is a fundamental component for the success of ARTs. Traditionally, this evaluation has relied on sperm parameters assessed by microscopy in a subjective manner (Rodríguez‐Martínez 2003). Nevertheless, numerous studies have demonstrated that such evaluations provide limited predictive capacity with respect to individual fertility (Gadea et al. 2004; Petrunkina et al. 2007). These classical approaches include parameters such as sperm concentration, motility and morphology. Although useful as a first‐line screening tool to discard low‐quality samples, they do not adequately reflect sperm functional competence. In response to this limitation, and with the aim of reducing the variability inherent to subjective assessments, more objective methodologies have been developed. Among these, CASA systems have represented a major advance in sperm quality evaluation (Kathiravan et al. 2011; Van de Hoek et al. 2022). These systems not only quantify the proportion of motile spermatozoa but also provide a range of kinematic parameters that characterize individual movement patterns. These include curvilinear velocity (VCL), straight‐line velocity (VSL), average path velocity (VAP, all expressed in μm/s), as well as beat‐cross frequency (BCF, Hz) and amplitude of lateral head displacement (ALH, μm). In addition, derived indices such as straightness (STR = VSL/VAP, %), linearity (LIN = VSL/VCL, %) and wobble (WOB = VAP/VCL, %) are provided. The use of CASA has also enabled the identification of specific motility and kinematic parameters associated with the fertilization ability of a sperm sample. In rams, significant relationships between VCL and VAP and in vivo fertility have been reported using frozen–thawed semen (Del Olmo et al. 2013). In bulls, parameters such as VSL, LIN and STR have shown predictive value for fertility after thawing (Gliozzi et al. 2017), whereas in boars, VCL, VSL and STR have been associated with conception rate and litter size after 2 h of incubation at 39°C (Holt et al. 1997).

In addition to fertility prediction, CASA systems have facilitated the identification of motility patterns relevant to sperm physiology, such as hyperactivation. This pattern is characterized by increased VCL and ALH and reduced LIN and is associated with sperm capacitation (Del Olmo et al. 2016; Peris‐Frau et al. 2021; Štiavnická et al. 2023). In parallel, higher velocities have been linked to increased metabolic activity in bovine spermatozoa (Boni et al. 2017), while specific changes in motility and kinematic parameters have been linked to alterations in plasma membrane and acrosomal integrity (Amann and Waberski 2014; Holt and Van Look 2004). In this regard, studies in bulls have shown that spermatozoa with intact plasma membrane and acrosome exhibit higher motility, while those with acrosomal damage display reduced or absent movement, supporting a functional association between motility patterns and structural integrity (Yániz et al. 2017).

Among the advances derived from CASA application, the study of sperm heterogeneity has represented a substantial improvement in the precision of semen quality evaluation (Maroto‐Morales et al. 2016; Ramón et al. 2014). Increasing evidence indicates that ejaculates are not homogeneous populations but rather consist of distinct sperm subpopulations differing in motility and morphometric features, which exhibit different functional behaviours (García‐Álvarez et al. 2014; Muiño et al. 2008; Ramón et al. 2013). Studies in rams have shown that fertility is not related to average sperm head dimensions but rather to ejaculate heterogeneity, with a higher proportion of spermatozoa exhibiting short and elongated heads being strongly associated with increased fertility rates (Maroto‐Morales et al. 2015). In contrast, in boars, specific sperm head morphometric parameters, such as length, ellipticity, elongation and regularity, have shown predictive capacity for litter size, whereas the distribution of morphometric subpopulations was not associated with fertility outcomes (Barquero et al. 2021). Meanwhile, in bulls, differences in sperm head morphometry, such as shape factor, symmetry and Fourier descriptors, have been linked to variations in field fertility among sires, even in the absence of differences in conventional semen quality parameters (Riveros et al. 2023).

These findings have not only enabled the identification of sperm subpopulations associated with higher fertility but have also been applied to studies on sperm resilience or sensitivity to cryopreservation, allowing the identification of good and poor freezers (Ramón et al. 2013). This knowledge is of particular relevance for the reliable storage of sperm samples in genetic resource banks and their subsequent use in ARTs such as AI or in vitro embryo production within breeding programs in domestic species (Tamargo et al. 2019).

The need to monitor sperm heterogeneity has driven the development and implementation of analytical tools capable of providing a more comprehensive evaluation of sperm function at the individual cell level (Ortega‐Ferrusola et al. 2017). In this regard, flow cytometry has become a key complementary technique, as it enables rapid, objective and multiparametric analysis of large sperm populations, providing a functional insight into this heterogeneity (Peris‐Frau et al. 2021). Its application across species has yielded relevant information on multiple aspects of sperm physiology, including membrane dynamics, mitochondrial function, acrosomal status and chromatin integrity (Martínez‐Pastor et al. 2010).

From a methodological perspective, flow cytometry is based on the analysis of the physical properties of cells through light scattering parameters, primarily forward scatter (FSC), associated with cell size, and side scatter (SSC), which reflects internal complexity (Martínez‐Pastor et al. 2010). Although spermatozoa exhibit a highly specialized and relatively uniform morphology, these signals allow discrimination of cell populations, removal of debris and exclusion of aggregates or non‐sperm events through appropriate gating strategies. Moreover, the combined use of FSC and SSC constitutes the essential first step in any cytometric analysis, as it defines the population to which subsequent fluorescence‐based evaluations will be applied (Peña et al. 2018). In this context, recent advances in imaging flow cytometry have enabled a more precise characterization of sperm heterogeneity by allowing the specific identification of the subcellular localization of detected signals (Peris‐Frau et al. 2020; Iniesta‐Cuerda et al. 2025). For example, during capacitation, protein tyrosine phosphorylation increases predominantly along the flagellum in ovine spermatozoa, a dynamic redistribution that can be accurately captured using imaging flow cytometry (Peris‐Frau et al. 2020). Similarly, protein acetylation exhibits a broader distribution across the head, midpiece and tail in boar spermatozoa, later becoming mainly confined to the head following the acrosome reaction, a shift that can likewise be resolved at the subcellular level using this approach (Iniesta‐Cuerda et al. 2025). Although imaging flow cytometry provides valuable information in research settings by combining cytometric throughput with image‐based localization, its cost, technical requirements, and data‐management need currently limit its use in routine semen quality control and field practice. Therefore, in the context of domestic animal reproduction, this technology should be considered mainly as a research and biomarker‐validation tool rather than as an immediately applicable option for practicing veterinarians under field conditions.

Once the population of interest has been defined, the multiparametric nature of flow cytometry requires careful selection of the probe combinations and sample preparation strategy. Analyses can be performed on non‐fixed cells to evaluate dynamic functional attributes, or on fixed and permeabilized samples when intracellular structures or molecular targets need to be assessed. Live‐cell approaches are particularly useful for monitoring plasma membrane integrity, acrosomal status, mitochondrial activity, membrane lipid disorder, oxidative stress and reactive oxygen species production. In contrast, fixed or permeabilized approaches allow the evaluation of DNA damage, oxidative DNA lesions, chromatin packaging, chromatin condensation and protein localization (García‐Macías et al. 2006; Del Olmo et al. 2015, 2016; Peris‐Frau et al. 2020; Ribas‐Maynou et al. 2021; Soria‐Meneses et al. 2022). Consequently, the integration of analyses in non‐fixed cells with those requiring fixation and permeabilization has enabled a shift from purely descriptive assessments towards approaches capable of monitoring key functional events in spermatozoa. In line with this evolution, functional assays have been developed to more directly evaluate the ability of spermatozoa to accomplish essential processes during fertilization (Rodríguez‐Martínez 2003). These include the assessment of sperm capacitation (Peris‐Frau et al. 2020, 2021), acrosome reaction (Iniesta‐Cuerda et al. 2025), zona pellucida binding or penetration assays (Soler and Garde 2003), and, in a more integrative manner, in vitro fertilization systems (García‐Álvarez, Maroto‐Morales, Martínez‐Pastor, Garde, et al. 2009; García‐Álvarez, Maroto‐Morales, Martínez‐Pastor, Fernández‐Santos, et al. 2009). These assays provide a closer approximation to sperm fertilizing competence. However, they remain constrained by the inherent limitations of in vitro systems, which fail to fully reproduce the complexity of the physiological environment of the female reproductive tract. Under in vivo conditions, spermatozoa interact with the uterine and oviductal epithelium, as well as with EVs secreted by these tissues (Gervasi et al. 2020), establishing a network of signals and regulatory mechanisms that have not yet been fully replicated in vitro. These interactions play a key role in regulating sperm function, ensuring that only specific subpopulations acquire the capacity to undergo capacitation and reach the site of fertilization (Ardon et al. 2016; Pérez‐Cerezales et al. 2018).

To overcome these limitations, various strategies have been developed to bring in vitro conditions closer to the physiological environment. Notable among these are the use of conditioned culture media (Hosseinabadi et al. 2025) and, more recently, the incorporation of secreted EVs (Lange‐Consiglio et al. 2022), as well as the development of more complex models, such as co‐culture systems with oviductal cells and microfluidic devices (Abdel‐Ghani et al. 2020; Camara Pirez et al. 2021; Nagata et al. 2018; Silva et al. 2025). These approaches allow for a more accurate reproduction of the physiological conditions in which spermatozoa must perform their function, thereby facilitating a more precise assessment of their fertilizing capacity. The different approaches currently available for semen quality assessment differ considerably in the type of information they provide, their level of complexity, and their applicability in research and routine practice. Table 2 summarizes the main semen evaluation approaches, their strengths, limitations and applications.

TABLE 2.

Comparative interpretation of semen evaluation approaches in domestic species.

Field	Information
Approach	Subjective microscopy
Parameters assessed	Mass motility, individual motility, morphology, concentration
Main strengths	Low cost; practical under field conditions; useful for rapid first‐line screening
Limitations	Strongly operator‐dependent; limited precision; limited fertility prediction
Most appropriate use	Initial acceptance or rejection of ejaculates; field breeding soundness evaluation
Approach	CASA
Parameters assessed	Motility, kinematics, subpopulations and morphometry
Main strengths	Objective, rapid and quantitative; identifies sperm heterogeneity
Limitations	Sensitive to acquisition settings; limited inter‐laboratory comparability
Most appropriate use	Routine evaluation, advanced motility analysis and research
Approach	Flow cytometry
Parameters assessed	Membrane and DNA integrity, acrosomal and mitochondrial status, oxidative stress
Main strengths	High‐throughput and multiparametric single‐cell analysis
Limitations	Requires standardization; limited inter‐laboratory comparability
Most appropriate use	Mechanistic studies and biomarker validation
Approach	Imaging flow cytometry/automated image analysis
Parameters assessed	Morphology, protein localization and fluorescence imaging
Main strengths	Combines imaging and flow cytometry; analyzes sperm heterogeneity
Limitations	High cost; specialized expertise; limited routine use
Most appropriate use	Research, biomarker validation and advanced morphology analysis
Approach	Functional assays
Parameters assessed	Capacitation, acrosome reaction, sperm–oocyte interaction and IVF
Main strengths	Provide a closer approximation to fertilizing competence
Limitations	Time‐consuming; species‐specific; limited physiological relevance
Most appropriate use	Validation of candidate biomarkers and mechanistic studies of fertilization
Approach	Omics approaches
Parameters assessed	Proteome, metabolome, epigenome, snc RNAs, extracellular vesicle cargo
Main strengths	Identifies pathways and candidate biomarkers
Limitations	High cost; bioinformatics and validation required
Most appropriate use	Biomarker discovery and mechanistic studies
Approach	Artificial intelligence/machine learning
Parameters assessed	Classification and prediction from CASA, cytometry, imaging and omics
Main strengths	Integrates multidimensional data; reduces observer bias
Limitations	Risk of overfitting; requires external validation; fertility endpoints remain limited
Most appropriate use	Decision support after external validation

4.1. Methodological Limitations, Reproducibility and Translational Value of Semen Assessment

Although semen evaluation has progressively moved from subjective microscopic examination to more objective and multiparametric approaches, its ability to predict fertility under practical conditions remains limited. Fertility is not determined by sperm quality alone, but by the interaction of multiple factors, including the female reproductive status, timing of insemination, sperm dose, semen processing, extender composition, storage conditions and farm management. For this reason, conventional semen parameters usually explain only part of the variation observed in field fertility. No single in vitro endpoint should therefore be considered a universal fertility biomarker. A more realistic approach is to combine complementary indicators of sperm performance, including motility, structural integrity, functional status, and, whenever possible, fertility records obtained under clearly defined artificial insemination conditions (Rodríguez‐Martínez 2003; Petrunkina et al. 2007; Gliozzi et al. 2017).

Computer‐assisted sperm analysis (CASA) has greatly improved the objectivity and resolution of motility assessment. However, CASA‐derived values are strongly influenced by technical and analytical conditions. Frame rate, chamber depth, sperm concentration, temperature, dilution medium, microscope configuration, software version, and threshold settings can all affect the final kinematic output. As a result, values obtained in different laboratories, or even with different CASA systems, are not always directly comparable. This limitation is particularly relevant when comparing species because sperm dimensions, velocity patterns, trajectory characteristics, seminal plasma viscosity, and the biological interpretation of hyperactivation differ markedly among domestic mammals. Accordingly, CASA studies should provide detailed information on acquisition and analysis settings, and fertility‐related thresholds should not be extrapolated across species, laboratories, or collection methods without proper external validation (Amann and Waberski 2014; Mortimer et al. 2015; Valverde et al. 2020).

Similar considerations apply to flow cytometry. This technique offers rapid, high‐throughput, single‐cell information and is particularly useful for evaluating sperm heterogeneity. Nevertheless, its reproducibility depends on several methodological variables, including sample dilution, fixation or permeabilization procedures, fluorochrome concentration, incubation conditions, laser configuration, compensation strategy, gating design, debris exclusion, and the criteria used to define positive and negative populations. These issues are especially important in sperm analysis because spermatozoa are small, highly specialized cells with an elongated morphology and high sensitivity to handling. The use of appropriate viability controls, single‐stained controls, fluorescence‐minus‐one controls when required, standardized gating strategies, and complete methodological reporting in line with MIFlowCyt principles would improve reproducibility and make comparisons among studies more robust (Lee et al. 2008; Martínez‐Pastor et al. 2010; Peña et al. 2018).

Another important limitation is the restricted validation of many proposed fertility biomarkers. In many cases, candidate markers have been tested within a single breed, ejaculate type, extender, storage protocol, or fertility dataset. Therefore, their predictive value may not be maintained when they are applied to different populations or production systems. Moreover, biomarkers associated with post‐thaw sperm survival are not necessarily the same as those required for sperm transport through the female tract, oviduct binding, capacitation, fertilization, or early embryo development. Future studies should place greater emphasis on independent validation, blinded classification of fertility groups, harmonized analytical workflows, and biologically meaningful endpoints, rather than relying only on statistical associations.

4.2. Recent Advances: Omics, Artificial Intelligence and Machine‐Learning‐Assisted Sperm Analysis

Recent omics studies have reinforced the idea that the method used for semen collection is not a neutral pre‐analytical factor. In bulls, proteomic analyses have shown that seminal plasma profiles differ between ejaculates obtained by artificial vagina and electroejaculation, reflecting different relative contributions from the epididymis and accessory sex glands (Rego et al. 2015). More recent proteomic and metabolomic studies in goat bucks have reported collection method‐related differences in pathways involved in energy metabolism, oxidative phosphorylation, membrane organization and cryotolerance. These findings support the view that semen quality should be interpreted in relation to the biochemical environment generated by each collection procedure, rather than considering the sperm cell in isolation (Li et al. 2024; Lv et al. 2024, 2025).

Multi‐omics and computational approaches are also opening new possibilities for identifying fertility‐associated signatures. For instance, the combined analysis of genetic, epigenetic and small RNA information has been proposed as a strategy for discovering biomarkers of bull fertility (Costes et al. 2024). However, these approaches should still be interpreted with caution. In most cases, omics‐derived markers remain at the discovery stage and require validation in independent populations, ideally with links to interpretable biological mechanisms. This is particularly important in domestic species, where fertility estimates are influenced not only by the male but also by herd management, female reproductive status, semen dose, insemination timing and the reproductive technology applied.

Artificial intelligence and machine‐learning‐based tools provide a complementary opportunity to improve semen assessment. These methods can integrate large numbers of kinematic, cytometric, morphometric, image‐derived and omics variables, and may detect patterns that are difficult to identify using conventional statistical approaches. In Holstein bulls, machine‐learning models have been applied to large datasets to predict sperm quality traits (Hürland et al. 2023). Deep‐learning approaches are also being developed for bovine sperm morphology assessment using conventional microscopy images or label‐free imaging flow cytometry, with the potential to increase analytical throughput and reduce observer dependence (Sevilla et al. 2025; Umirbaeva et al. 2026). Nevertheless, their practical use still depends on rigorous validation. Model performance can be affected by dataset size, class imbalance, image acquisition conditions, annotation quality, breed representation and the availability of reliable fertility endpoints. At present, artificial‐intelligence‐assisted sperm analysis should therefore be viewed as a decision‐support tool, rather than as a substitute for standardized laboratory assessment and biologically validated measures of fertility.

4.3. Practical Integration of Semen Collection and Quality Control in Artificial Insemination Centers and Field Conditions

The choice of a semen assessment method should be adapted to the context in which the sample is collected and processed. In artificial insemination centres, semen collection is usually part of a standardised workflow involving trained personnel, conditioned males, controlled artificial vagina preparation, hygienic handling, temperature control and rapid dilution or processing. Under these conditions, objective methods such as CASA and flow cytometry can be incorporated into routine quality control. By contrast, imaging flow cytometry, omics and artificial‐intelligence‐assisted approaches are currently better suited to research, biomarker validation and problem‐solving in specialised laboratories.

Field conditions require a different approach. Breeding soundness evaluation, emergency germplasm recovery, and semen collection from extensively managed, untrained, or clinically compromised males are often performed with limited equipment, variable temperature control, and little access to advanced laboratory instruments. In this context, conventional assessments of motility, concentration and morphology remain useful because they are inexpensive, robust and immediately interpretable. Portable or mobile CASA systems, including smartphone‐ or tablet‐based devices, may provide an intermediate option by offering more objective information on motility and concentration close to the animal. However, their results should be validated for each species, diluent, temperature range, and operator before they are used to support clinical or reproductive decisions (Buss et al. 2019; Dini et al. 2019; Domain et al. 2022; Matamoros et al. 2025).

Therefore, semen collection and quality control should be planned together rather than as separate steps. A sophisticated analytical method may add little value if the sample has been collected or transported under poorly controlled conditions. Conversely, a simple field test may be sufficient when the immediate objective is to decide whether an ejaculate should be accepted, rejected, diluted, cooled, frozen, or used without delay. Future protocols should therefore describe the collection setting, available infrastructure and intended use of the semen, as these factors determine which evaluation methods are realistic and how their results should be interpreted.

5. Conclusion

In conclusion, sperm collection and evaluation methods have evolved substantially, providing a wide range of tools to support ARTs across domestic species. Each collection technique differentially influences sperm quality, largely through its impact on seminal plasma composition and sperm functional state. Advances in objective and multiparametric sperm assessment have improved the understanding of sperm heterogeneity and fertility potential beyond conventional parameters. Therefore, the careful selection and optimization of both collection and evaluation methodologies remain critical to maximizing reproductive outcomes and the effective preservation of genetic resources.

Author Contributions

A.J. Soler: writing original draft and writing review, conceptualization, funding acquisition, project administration, supervision, validation. O. García‐Álvarez, M. Iniesta‐Cuerda and M. Neila‐Montero: writing review and editing. P. Jiménez‐Rabadán, A. Maroto‐Morales, V. Montoro and M.R. Fernández‐Santos: investigation. J.J. Garde: funding acquisition, project administration, supervision, validation and review.

Funding

This work was supported by Junta de Comunidades de Castilla‐La Mancha, PIB‐05‐011, PCC08‐0105; Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, RTA2005‐00091‐CO2‐01, RZ2006‐00006‐CO3‐01, RZ2008‐0009‐CO2, RZ2012‐00013‐CO2.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.